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Computer Vision Research Progress
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Editors: Zhongkai Zhu
Book Description:
Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images. The image data can take many forms, such as a video sequence, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision seeks to apply the theories and models of computer vision to the construction of computer vision systems. Examples of applications of computer vision systems include systems for controlling processes (e.g. an industrial robot or an autonomous vehicle). Detecting events (e.g. for visual surveillance). Organizing information (e.g. for indexing databases of images and image sequences), Modeling objects or environments (e.g. industrial inspection, medical image analysis or topographical modeling), Interaction (e.g. as the input to a device for computer-human interaction). Computer vision can also be described as a complement (but not necessarily the opposite) of biological vision. In biological vision, the visual perception of humans and various animals are studied, resulting in models of how these systems operate in terms of physiological processes. Computer vision, on the other hand, studies and describes artificial vision system that are implemented in software and/or hardware. Interdisciplinary exchange between biological and computer vision has proven increasingly fruitful for both fields. Sub-domains of computer vision include scene reconstruction, event detection, tracking, object recognition, learning, indexing, ego-motion and image restoration. This new book presents leading-edge new research from around the world.

Table of Contents:

Chapter 1 - Application of Stereo-Computer Vision Techniques to High Sensitivity Measurement of Shape and Deformation of Solid Bodies, pp. 1-46;
(Eustachio Cosola, Katia Genovese, Luciano Lamberti and Carmine Pappalettere)

Chapter 2 - A Follow-up of Image Registration Techniques For Application in Digital Subtraction Angiography, pp. 47-81;
(Y. Bentoutou and N. Taleb)

Chapter 3 - Intelligent Video Analysis for Traffic Surveillance by Perceptual Edge Feature Grouping, pp. 83-107;
(Huiqiong Chen and Qigang Gao)

Chapter 4 - Accurately Calibrating Image Distortion Center of Radial Camera, pp. 109-140;
(Zhijun Dai, Feng Zhang, Yihong Wu and Zhanyi Hu)

Chapter 5 - Twin Object-centered Models for 3D Reconstruction, pp, 141-166;
(Xin Liu and Hongxun Yao)

Chapter 6 - Fast Face Detector and Recognition for Biometrical Security System, pp. 167-183;
(Jose M. Chaves-González, Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido and Juan M. Sánchez-Peréz)

Chapter 7 - Joint Rotation, Shift and Scale Invariant Feature Extraction for Content-Based Image Retrieval, pp. 185-211;
(Chi-Man Pun)

Chapter 8 - Application of Computer Vision in Shortest Path Planning, pp. 213-244;
(Frank Y. Shih)

Chapter 9 - Object Detection and Tracking Using Bayes-Constrained Particle Swarm Optimization, pp. 245-260;
(Yuhua Zheng and Yan Meng)

Chapter 10 - Head Pose Estimation and Multi-View Face Recognition with Nonlinear Dimensionality Reduction Methods, pp. 261-277;
(Bisser Raytchev, Ikushi Yoda and Katsuhiko Sakaue)

Chapter 11 - Evidence-Based Pixel Labeling for Color Image Segmentation, pp. 279-296;
(Patrick Vannoorenberghe, Ludovic Macaire and Olivier Colot)

Chapter 12 - E-Quality for Manufacturing (EQM) Using Internet-based Computer Vision System, pp. 297-313;
(Yongjin (James) Kwon, Richard Chiou and Gi-Nam Wang)

Chapter 13 - Evaluation and Assessment of Rigid, Affine, and Nonrigid Registration Techniques: Application to X-ray Angiography Images, pp. 315-326;
(N. Taleb, Y. Bentoutou and K. Kpalma)


   Binding: Hardcover
   Pub. Date: 2008 4th Quarter
   ISBN: 978-1-60021-992-4
   Status: AV
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
PR At Prepress
AP At Press
AV Available
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Computer Vision Research Progress